Artificial intelligence and machine learning: Top courses, skills, salaries and careers

In 2022, the scope of Artificial intelligence (AI) and machine learning will continue to grow as more businesses adopt these technologies.

AI/ML is already used in many industries, such as healthcare, finance, manufacturing, and retail. As these technologies become more advanced, they will likely be used in more industries.

For example, AI could help plan city infrastructure or optimize traffic patterns. The demand for AI/ML skills will continue to grow in 2022. As businesses adopt these technologies, they will need employees who know how to use them. There are many ways to learn AI and machine learning, such as taking online courses or attending conferences.

The salaries for AI/ML jobs will continue to rise in 2022. With the demand for these skills increasing, employers will be willing to pay more for employees who have them. In addition, as AI and machine learning technologies become more commonplace, workers with these skills will be in high demand globally.

Significance of AIML courses in today’s era

In today’s era, Artificial intelligence (AI) and machine learning are two of the hottest topics in the tech industry. There is a lot of hype around AI and machine learning and for a good reason. These technologies have the potential to revolutionize many industries and change the way we live.

AI and machine learning are already being used in several ways, such as improving search results on Google, identifying plagiarism, and helping doctors diagnose diseases. As these technologies continue to develop, they will become even more integrated into our lives.

e-learning training programs

That’s why it’s essential to learn machine learning now. If you want to stay ahead of the curve and be prepared for the future, then you need to understand these technologies. Luckily, several excellent courses can teach you everything you need to know about AI and machine learning.

Some skills you learn during an AI, or machine learning course include:

  • Statistical methods: You will learn about different statistical methods used for data analysis. This is important for understanding how machine learning algorithms work.
  • Programming: Most courses will teach you how to code in one or more programming languages. This is necessary for implementing machine learning algorithms.
  • Linear algebra: This branch of mathematics is essential for understanding how matrix operations work in machine learning.
  • Calculus: Differential equations are used extensively in machine learning!

Career scope after Artificial intelligence course?

Numerous career opportunities are available for those who complete a course in artificial intelligence (AI) and machine learning. With the right skillset, you could pursue a role as a data scientist, software engineer, research scientist, or business intelligence analyst, to name just a few potential positions.

Data scientists are in high demand across almost all industries, as they play a vital role in extracting insights from large data sets. AI and machine learning are essential tools for data scientists, so if you have these skillsets, you will be well-placed to pursue this career path.

Software engineering, research scientists and business intelligence are other popular career choices for those with AI and machine learning skills. These roles suit those with strong analytical & mathematical skills.

Learn and Grow with Imarticus Learning:

Imarticus Learning offers a PG program in Data Analytics & Machine Learning, an assured placement postgraduate program built for future data science experts. Students learn real-world applications of data science & build predictive models.

Why this Course:

Artificial Intelligence Training: Grasp foundations of AIML and learn the data science tools and be job-ready. 

Placement: The course comes with an excellent job assurance.

Best learning input: Live instructor-led sessions to provide the best student outcomes.

Practical Approach: Master skills through real-world projects, hackathons, capstone projects and mock interviews.

Contact the Live Chat Support system or visit our Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, Gurgaon, and Ahmedabad training centres.

Here’s how to create your first desktop application in python

Most young developers have questions about creating desktop software using python. But before going into the process of developing a desktop application, they should learn python programming beforehand to learn concepts related to python.

Step By Step Guide to Create a GUI App in Python

Step 1

In this step, define the current task. Deciding what needs to be solved with the application explains further steps. The field has a variety of usage, for example, Data Visualizations, personal application performance to work with images, text, Business automation GUI’s for managing tasks, and developing systems and monitoring.

best ai and ml coursesPrimary estimation of the functionality and size of the application is necessary as it will help choose the best-suited GUI tool kit.

In case you are not familiar with Graphical User Interface (GUI), it is recommended to take any of the available AI and machine learning courses to clear the fundamentals.  

Step 2   

Choose the correct GUI package and play around with it using python. There are multiple Python-based packages available to do this. One of the easiest ways to do so is by using Tkinter. It allows developers to create small and simple applications using a GUI interface. Popular third-party packages include PyQt, Kivy, WxPython, and Pyside. To know about these, individuals can look at the Python desktop application development tutorial.

Step 3

Here PyQt5 is used as a GUI toolkit for the desktop application. Next, download and install the package.

Step 4 

Then create a pyqt_app1.py file to import PyQt5 modules. After creating PyqtApp class, in the _init_function, in the bottom, create and import instruction with a file name with if _name+ == “_main”: and type lines with calling pyqt based app, importing sys module, calling show () to start the GUI application.

from PyQt5 import QtWidgets, QtGui, QtCore

class PyQtApp(QtWidgets.QWidget):

   

    def __init__(self, parent=None):

        QtWidgets.QWidget.__init__(self, parent)

        self.setWindowTitle(“PyQt Application”)

        self.setWindowIcon(QtGui.QIcon(“Your/image/file.png”))

 

if __name__ == “__main__”:

    import sys

    app = QtWidgets.QApplication(sys.argv)

    myapp = PyQtApp()

    myapp.show()

    sys.exit(app.exec_())

 

Step 5

Then add some style, font, and position of the application. Change the background colour by altering the line – self.element.setStyleSheet(“background-color: #hex number or rgba(). But to position the window, a desktop resolution is required. But this can be done by using multiple codes.

from PyQt5 import QtWidgets, QtGui, QtCore

class PyQtApp(QtWidgets.QWidget):

   

    def __init__(self, parent=None):

        QtWidgets.QWidget.__init__(self, parent)

        self.setWindowTitle(“PyQt Application”)

        self.setWindowIcon(QtGui.QIcon(“Your/image/file.png”))

        self.setMinimumWidth(resolution.width() / 3)

        self.setMinimumHeight(resolution.height() / 1.5)

        self.setStyleSheet(“QWidget {background-color:

                           rgba(0,41,59,255);}

                           QScrollBar:horizontal {

                           width: 1px; height: 1px;

                           background-color: rgba(0,41,59,255);}  

                           QScrollBar:vertical {width: 1px;

                           height: 1px;

                           background-color: rgba(0,41,59,255);}”)

 

if __name__ == “__main__”:

    import sys

    app = QtWidgets.QApplication(sys.argv)

    desktop = QtWidgets.QApplication.desktop()

    resolution = desktop.availableGeometry()

    myapp = PyQtApp()

    myapp.setWindowOpacity(0.95)

    myapp.show()

    myapp.move(resolution.center() – myapp.rect().center())

    sys.exit(app.exec_())

else:

    desktop = QtWidgets.QApplication.desktop()

    resolution = desktop.availableGeometry()

 

Step 6

In this step, adding functionality to the app is necessary. After all, while solving tasks, a graphical interface will make the user comfortable using the application. We can also add frames, fields, buttons and other graphics into the application. Using buttons and text fields will provide good and effective results. For best view buttons, here is how to create a new class for the application with styling and font.

from PyQt5 import QtWidgets, QtGui, QtCore

font_but = QtGui.QFont()

font_but.setFamily(“Segoe UI Symbol”)

font_but.setPointSize(10)

font_but.setWeight(95)

 

class PushBut1(QtWidgets.QPushButton):

   

    def __init__(self, parent=None):

        super(PushBut1, self).__init__(parent)

        self.setMouseTracking(True)

        self.setStyleSheet(“margin: 1px; padding: 7px;

                           background-color: rgba(1,255,0,100);

                           color: rgba(1,140,0,100);

                           border-style: solid;

                           border-radius: 3px; border-width: 0.5px;

                           border-color: rgba(1,140,0,100);”)

   

    def enterEvent(self, event):

        self.setStyleSheet(“margin: 1px; padding: 7px;

                           background- color: rgba(1,140,040,100);

                           color: rgba(1,140,255,100);

                           border-style: solid; border-radius: 3px;

                           border-width: 0.5px;

                           border-color: rgba(1,140,140,100);”)

   

    def leaveEvent(self, event):

        self.setStyleSheet(“margin: 1px; padding: 7px;

                           background-color: rgba(1,255,0,100);

                           color: rgba(1,140,0,100);

                           border-style: solid;

                           border-radius: 3px; border-width: 0.5px;

                           border-color: rgba(1,140,0,100);”)

class PyQtApp(QtWidgets.QWidget):

   

    def __init__(self, parent=None):

        QtWidgets.QWidget.__init__(self, parent)

        self.setWindowTitle(“PyQt Application”)

        self.setWindowIcon(QtGui.QIcon(“Your/image/file.png”))

        self.setMinimumWidth(resolution.width() / 3)

        self.setMinimumHeight(resolution.height() / 1.5)

        self.setStyleSheet(“QWidget

                           {background-color: rgba(1,255,0,100);}

                           QScrollBar:horizontal

                           {width: 1px; height: 1px;

                           background-color: rgba(0,140,0,255);}

                           QScrollBar:vertical

                           {width: 1px; height: 1px;

                           background-color: rgba(0,140,0,255);}”)

        self.textf = QtWidgets.QTextEdit(self)

        self.textf.setPlaceholderText(“Results…”)

        self.textf.setStyleSheet(“margin: 1px; padding: 7px;

                                 background-color:      

                                 rgba(1,255,0,100);

                                 color: rgba(1,140,0,100);

                                 border-style: solid;

                                 border-radius: 3px;

                                 border-width: 0.5px;

                                 border-color: rgba(1,140,0,100);”)

        self.but1 = PushBut1(self)

        self.but1.setText(“”)

        self.but1.setFixedWidth(72)

        self.but1.setFont(font_but)

        self.but2 = PushBut1(self)

        self.but2.setText(“”)

        self.but2.setFixedWidth(72)

        self.but2.setFont(font_but)

        self.but3 = PushBut1(self)

        self.but3.setText(“”)

        self.but3.setFixedWidth(72)

        self.but3.setFont(font_but)

        self.but4 = PushBut1(self)

        self.but4.setText(“”)

        self.but4.setFixedWidth(72)

        self.but4.setFont(font_but)

        self.but5 = PushBut1(self)

        self.but5.setText(“”)

        self.but5.setFixedWidth(72)

        self.but5.setFont(font_but)

        self.but6 = PushBut1(self)

        self.but6.setText(“”)

        self.but6.setFixedWidth(72)

        self.but6.setFont(font_but)

        self.but7 = PushBut1(self)

        self.but7.setText(“”)

        self.but7.setFixedWidth(72)

        self.but7.setFont(font_but)

        self.grid1 = QtWidgets.QGridLayout()

        self.grid1.addWidget(self.textf, 0, 0, 14, 13)

        self.grid1.addWidget(self.but1, 0, 14, 1, 1)

        self.grid1.addWidget(self.but2, 1, 14, 1, 1)

        self.grid1.addWidget(self.but3, 2, 14, 1, 1)

        self.grid1.addWidget(self.but4, 3, 14, 1, 1)

        self.grid1.addWidget(self.but5, 4, 14, 1, 1)

        self.grid1.addWidget(self.but6, 5, 14, 1, 1)

        self.grid1.addWidget(self.but7, 6, 14, 1, 1)

        self.grid1.setContentsMargins(7, 7, 7, 7)

        self.setLayout(self.grid1)

 

if __name__ == “__main__”:

    import sys

    app = QtWidgets.QApplication(sys.argv)

    desktop = QtWidgets.QApplication.desktop()

    resolution = desktop.availableGeometry()

    myapp = PyQtApp()

    myapp.setWindowOpacity(0.95)

    myapp.show()

    myapp.move(resolution.center() – myapp.rect().center())

    sys.exit(app.exec_())

else:

    desktop = QtWidgets.QApplication.desktop()

    resolution = desktop.availableGeometry()

Step 7

You can add a few more fields and explore the possibilities of PyQt.

Step 8

Then connect the buttons and functions for a calling event. For this, we need to add an additional line to the  _init_ function of the main class.

self.but1.clicked.connect(self.on_but1)

Step 9

You can add images in this step. The second button in the image will call the image file from the text to put it in the right bottom corner. 

Adding QLabel: 

self.lb1 = QtWidgets.QLabel(self)

self.lb1.setFixedWidth(72)

self.lb1.setFixedHeight(72)

 

Adding function:

def on_but2(self):

    txt = self.textf.toPlainText()

    try:

        img = QtGui.QPixmap(txt)

        self.lb1.setPixmap(img.scaledToWidth(72,

                           QtCore.Qt.SmoothTransformation))

    except:

        pass

To connect the second button and the function: 

self.but2.clicked.connect(self.on_but2)

Step 10

Complete and run the application. Apart from this PyQt has various other applications, and you can use those to create complete desktop applications.

 If you are not familiar with coding, you can learn python programming or enroll in any AI and machine learning courses. Apart from this, you can also look at the Python desktop application development tutorial

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How digitization through artificial intelligence and machine learning technologies has gained momentum post COVID-19?

In just a few months, the COVID-19 pandemic has managed to do what normal times would have taken years to achieve – a paradigm shift in the way companies in every industry and sector do business. Artificial intelligence and machine learning have been at the forefront during these challenging times. 

As the world gradually finds its way back to usual ways of life, it is interesting to see how the global crisis has paved the way for behavioral shifts, learning, and innovation. 

AI and ML in the Post-Covid-19 World

With the acceleration of digitization through Artificial Intelligence (AI) and Machine Learning (ML), digital sales have seen a boost, and businesses have focused their tech investments on cloud-based products and services. From online grocery stores and EdTech sites to online pharmacies and OTT players, the post-COVID-19 world looks very different through the AI and ML lens.

So, here are some examples to show how AI and ML technologies have gained momentum post-COVID-19:

  • AI and ML have been impacting the healthcare industry since long before the pandemic hit. AI algorithms have and continue to help in quickly sifting through large datasets to help identify similar diseases and their possible cures to accelerate the COVID-19 research work. 
  • AI and automation technology have also eased the healthcare sector’s administrative load by automating various processes. For example, data processing algorithms to extract data from internal systems and automatically generate medical reports and necessary audit trails have gained momentum post-pandemic. 
  • Also, advancements in ML will continue to help create new revenue streams. For example, scientists, drug researchers, and pharma companies are increasingly turning to AI and ML data processing algorithms to facilitate vaccine and drug discovery and their possible impacts on people. 
  • Lockdowns and social distancing norms have boosted online markets and the digital economy. However, even when the pandemic is gradually ebbing, customers are expected to continue using doorstep services as they did during the peak crisis. Hence, technologies like Augmented Reality (AR) and Virtual Reality (VR) have increased among eCommerce platforms to deliver a better customer experience. 
  • Talking about customer experience, the online retail industry has ramped up its use of AI chatbots and smart assistants to attend to the ever-increasing numbers of digital customers. Hence, the use of AI has helped streamline digital services, online ordering, and delivery systems. 
  • The pandemic has given rise to a digital workforce. To this end, the use of AI to quickly process applications, scan for eligibility and qualifications and perform other mandatory hiring checks has become the norm and is only expected to increase in the near future. 
  • The financial sector has also seen a dramatic rise in the use of AI and automation to serve its customers better and quicker during challenging times. For instance, banks leverage AI to help customers safely upload documents, categorize them and expedite processes without any delay. 
  • Lastly, greater digitization has also increased the risks of cybersecurity threats during the pandemic. While conventional cybersecurity risk management systems have failed to keep up with evolving cyber threats, AI offers innovative defenses. The pandemic has only nudged organizations to adopt holistic approaches to cybersecurity through AI and ML and create an integrated security system. 

How to Find the Best Artificial Intelligence Course?

If you want to learn AI and get a certification in AI and ML, opting for an online course can be the best call. But before you sign up for the course, ensure that it offers hands-on experience with real-world projects and has a curriculum with extensive coverage of concepts related to machine learning, NLP, deep learning, data science, and computer vision. 

How Providers Can Use AI to Improve the Payment Integrity Process

Nowadays AI is utilized successfully and has proven to be an efficient, cost-effective, and reliable solution to cut down inappropriate payment claims worth a million dollars every year. The anomalies and patterns can be detected in less than a minute which helps to decrease fraud, system abuse, and future wastes.

From the provider’s point of view, they can be educated well to ensure evidence-based and high-quality alternatives. Learn more to know how the AIML program by Imarticus uses AI to improve the payment integrity process.

AI and Payment Integrity

A huge data volume from the providers, facilities, labs, etc. is integrated with AI-based computer power systems. This recognizes patterns in the data in a very effective and automatic way and helps to identify false claims. However, the billing behavior of the providers is difficult to detect as they are usually dealing directly with third-party enterprises for handling billing and coding issues.

This outsourcing may result in missing clarity and inconsistent processes which can ultimately lead to upcoding errors and fraudulent claims.

Thanks to the AI certification course, the identification of errors and fraud is a quick procedure with high precision and accuracy and the errors can be avoided drastically.

artificial intelligence and machine learning coursesInteroperability, APIs, and NLP Efficiency

The real innovation lies in the fact that the medical records of the patients can be directly obtained from the providers of EHRs with firm signed contracts.

This kind of interoperability helps in making the tasks work automatically like pre-authorization of the requests as per the need. This saves the manual working hours and makes the entire system run fluidly.

AI-based natural language processing (NLP) can further accelerate the time-saving process by around 40 percent when used on unfiltered data in the review stages. This helps in the augmentation of the staff efficiency and reduction of the costly human resources like nurses.

Integrating technologies like AI, NLP, robotic processing, and machine learning courses can give the payers the advantage of controlling the expenditure. Furthermore, it gives a helping hand to the providers to better manage the revenue systems to have a more unified and fluid cash flow within the system.

Prepayment cost avoidance model

One of the emerging trends of the industry is a significant shift to a prepayment from a post-payment cost avoidance model. It results in cost reduction related to reprocessing, reworking, and claim recoveries. But, the payers have to be super cautious when adopting this method as it is not yet well demonstrated and proven. Payment integrity based on AI is positioned very uniquely and this prepayment cost reduction model is close to becoming a reality in the industry soon.

Educating the providers

To overcome overutilization and fraud claims another approach that can be employed is their pre-detection by the providers themselves even before the claim submission. During the overpayment or appeal recovery process, the providers can be educated about the non-compliance, errors, overpayment issues, or the reasons for service rejection. This can increase the cooperation from the providers and helps decrease the number of appeals made.

On the same lines, AI-based technologies can analyze the data sets and send responses to the doctors, and list all the factors causing the denial of the claim and also about the unnecessary medical care as mentioned in the health plans.

Conclusion

Finally, analytics and solutions based on AI can ensure to cut down inappropriate claims significantly by identifying the wrong claims and acting upon them. Learn AI and improve the healthcare systems by making proper and efficient use of AI-based algorithms and methods.

Must-haves of an Average Machine Learning Certification to Become a Machine Learning Architect

ML (Machine Learning) is one of the most popular modern-day technologies. You must be aware of the applications of data science in retail, e-commerce, education, and many other industries. New-age technologies like ML and AI (Artificial Intelligence) form the base of data science operations. Many companies around the world have invested in adopting an ML strategy for their organization.

ML job roles like machine learning architect are widely popular among young enthusiasts. Young enthusiasts look for artificial intelligence and machine learning courses that can help them in launching a successful career. Read on to know about the must-haves of an ML certification course.

Importance of learning machine learning

The importance of learning machine learning in 2021 are as follows:

  • More and more businesses are inducing automation in their daily operations. Manual labor is being replaced by automated machines in the industry. However, for designing intelligent machines and algorithms, ML skills are required. The demand for skilled ML engineers is expected to increase exponentially in the coming years.
  • ML is a versatile modern-day technology used by many public sectors and industries. Smart ML algorithms are used in the regulation of public services like transportation, legal, healthcare, and education.
  • Since ML is a modern-day technology, there is a shortage of skilled ML architects/engineers in the industry. ML job roles in the industry offer lucrative salaries to ML professionals because of the expertise they bring to the table.
  • Machine learning is usually not used alone for industrial processes. Machine learning is coupled with other technologies like AI and deep learning to enhance productivity. You can also learn other new-age technologies by choosing a machine learning certification course.

Where to look for a machine learning certification course?

Colleges in India don’t provide a machine learning certification course. Generally, machine learning is a subject in any particular semester of a traditional degree program. Students cannot go through the entire college degree program if they just want to learn ML.

artificial intelligence and machine learning coursesOnline training is the best means of learning machine learning and AI. Also, online training is more accessible considering the scenario of the COVID pandemic.

Must-haves of an ML certification course

Want to become an ML architect? Choose an ML course that offers the following:

  • Machine learning is implemented for industry processes with the aid of several tools and technologies. Choose a machine learning/artificial intelligence course that covers tools/technologies like Pandas, Spyder, Colab, TensorFlow, NumPy, OpenCV, Python, and Jupyterhub.
  • The machine learning/artificial intelligence course should be endorsed by a reputed institution or EdTech platform. There is no point in wasting your money on an ML certification that is not recognized globally.
  • Besides covering the basics of machine learning and artificial intelligence, the online course should also cover other technologies that are used together. For example, technologies like deep learning and NLP are used with AI/ML.
  • Besides offering theoretical classes, a machine learning course should also provide an opportunity to work on real-life projects. Artificial intelligence and machine learning courses should also offer practical learning to enthusiasts.

 Which is the perfect course for ML enthusiasts?

 The Certification in Artificial Intelligence and Machine Learning by Imarticus Learning is the perfect ML course in 2021. This course is endorsed by IIT Guwahati, one of the top institutes in the country. This course will follow an industry-oriented syllabus that will help in knowing about the common industry practices. You can also opt for a demo class before choosing the ML certification course.

best artificial intelligence and machine learning courses from E&ICT Academy, IIT GuwahatiIn a nutshell

Getting an ML certification can boost your chances of getting placed in some of the top companies. You will also be in demand for the coming years by gaining an ML certification. Start your ML/AI certification program now!

How Is a Machine Learning Course Helping Secure Bright Careers?

Machine Learning (ML) is an emerging technology that has taken businesses by storm. Currently, more than 30% of businesses in India have already adopted machine learning technology or are planning to adopt it. Besides being termed as the ‘hottest job of the century’, ML job roles also offer lucrative salaries.

ML along with AI (Artificial Intelligence), plays a crucial role in data science operations. Young enthusiasts are looking for ML/AI courses that offer them industry-oriented learning. Read on to know how an ML course can aid in building a successful career.

Reasons to learn ML & AI

 The reasons one should look for an industry-oriented ML course are as follows:

  • The compound annual growth rate of the global ML market is more than 40%. Businesses are adopting ML/AI technologies on a large scale. There will be no shortage of ML job roles in the industry for the coming years. Also, the salaries of ML job roles in the industry are expected to increase in the coming years.
  • ML and AI are versatile technologies that are used by different sectors of the industry. ML/AI algorithms are also used for day-to-day operations in many public sectors. Sectors like healthcare, logistics, e-commerce, education, and retail use ML for their day-to-day operations.
  • Machine learning helps in building smart data analysis algorithms. You can gain meaningful insights from data analysis and understand your customers/clients better. Data analysis skills will also come in handy for making several real-life decisions.

Why go for online ML training?

Colleges in India usually do not provide a certification course in AI or ML. AI/ML is usually included in the traditional degree programs as a subject. You will have to go through the entire degree program to learn machine learning at a college. It is where online training allows you to learn machine learning without enrolling in a degree program. Also, the recent COVID pandemic made it difficult for young enthusiasts to attend classroom lectures.

artificial intelligence and machine learning coursesWorking professionals can commit to an online machine learning course depending upon their free hours. However, you will have to choose an effective machine learning course that makes you job-ready. Imarticus Learning is a reliable EdTech firm that offers industry-oriented machine learning and artificial intelligence course.

Why choose the ML course offered by Imarticus?

Imarticus Learning is a reputed EdTech platform that offers a Certification in Artificial Intelligence and Machine Learning in partnership with IIT Guwahati. This 9-months long certification program can help in preparing for numerous jobs like ML/AI engineer, data analyst, and data scientist. The reasons one should choose the AI/ML certification course are as follows:

  • ai and ml courses
    At the end of the course, you will receive a certificate endorsed by ITT Guwahati, one of the top educational institutions in India. The AI/ML certificate endorsed by IIT Guwahati will be globally recognizable. Also, you will get a 3-day campus immersion program with this course that allows you to interact with faculty members and peers of IIT Guwahati.
  • You will work on more than 100 assignments and 25 projects during the course. Real-life projects will aid in learning the ML industry practices.
  • Numerous AI/ML topics will be covered in this certification course. Some popular topics covered in this course are dimensionality reduction, unsupervised learning, deep learning, NLP, etc.
  • Towards the end of the machine learning and artificial intelligence course, you will compete in a hackathon to judge your AI/ML skills. You will also receive career support towards the end of the course from Imarticus.

In a nutshell

Imarticus has already placed many data scientists in some of the top organizations of the world. With their industry-oriented course curriculum, they will make you job-ready. Start your ML certification course now!

India Moves to Install an Automated Face Recognition System

What is Facial Recognition?

Facial recognition is a technique that allows the identification of an unknown person or helps determining a specific person’s identity just by using their face.

It is a part of artificial intelligence technology called computer vision. Facial recognition, however, is specialized and can come with baggage and some spoofing vulnerabilities for a few applicants.

How Does Facial Recognition Work Exactly?

Early automated face recognition systems depended on biometrics, like the distance between the person’s eyes, which would convert the two-dimensional features being measured into numbers that would help describe the face. This process of recognition involved comparing these vector values to the already known set in the database.

One complication that was faced in this initial technique was that it did not account for minor errors like head rotation and tilt as it was a more geometric approach.

artificial intelligence and machine learning coursesNow the software that is being focused on has a more photogenic approach,

allowing a more efficient three-dimensional facial recognition.

Things will be made much clearer, in this respect, to aspirants by taking up an artificial intelligence and machine learning course and will help them succeed in an artificial intelligence career.

What Does India Have in Mind For The Use of Automated Facial Recognition Software?

India, in a recent bid to automate the Indian criminal system and improve national security, has decided to implement an automated facial recognition system. This is being done starting with the headquarters of the NCRB in Mahipalpur.

Facial recognition has been a branch of artificial intelligence that has been strongly debated for a long time with a large number of skeptics worrying about the various threats that it can pose to privacy. The initial concerns included that facial recognition software if implemented completely can track the location and movement of citizens, giving this information to the government, without consent. These concerns have been dealt with and hence the software is now being put out.

An automated facial recognition system would be available to all the branches including state police, central forces, and central agencies which all fall under the central government.

According to the NCRB, the presence of an automated facial recognition system would serve as storage for criminal photographs while also facilitating a more efficient method to source out crime patterns and would allow a better understanding of criminal motives.

Using just one click of an icon on a mobile phone, crime fighters will be able to detect all of the criminal histories associated with a person from the automated facial recognition system database. It also has the ability to source out and collect data from a wide set of sources like CCTV footage and sound an alert if a blacklisted criminal is located.

It also updates the database by adding in new information and new pictures that it can collect through various forms of media like newspaper clippings, raids, sketches, and if a picture has been taken by a citizen.

This system may also help collect proof for crimes and thus aid the police and court in indicting a criminal quickly.

What Do AI & ML Engineers Do in Real World Scenarios?

Worldwide industries are identifying AI/ML engineers as one of the fastest-growing job titles. Since the trend is likely to last long, this means there are millions of opportunities for the present-day freshers and those planning a career. Here is all you need to know about what AI/ML Engineers are and what they do!

What Is an Artificial Intelligence and Machine Learning Engineer?

Over the past years, the role of an ML engineer has evolved. Typically, they are computer programmers, but their focus extends beyond programming to perform specific tasks that enable machines to take actions without being specifically directed to perform those tasks.

What does a Modern-day AI/ML engineer do?

Bridging Model-Building and Production

The general purpose of an ML engineer is to act as a bridge between the statistical & model-building work of data scientists & to build production-ready & robust AI/ML systems, platforms & services. The AI/ML Engineer use their knowledge of & combine it with programming and software engineering skills to enable easier use of and access to said models and analyses.

They may translate the work of data scientists from environments such as python/R notebooks analytics applications, automating model training & evaluation processes.

Improving Systems

AI/ML engineer is responsible for developing machine learning algorithms to improve systems or processes by automating tasks that otherwise would be physically executed. The job role demands skills in programming, analysis, & an understanding of tools & techniques used to apply AI/ML to real-world tasks. With the rapid increase in the use of ML, more programmers incline Machine Learning & AI courses that educate them in relevant techniques & tools.

Artificial Intelligence and Machine Learning coursesImproving Operational Efficiency

Machine learning engineers spend their time doing several things like exploring data, organizing, cleaning, and analyzing data to find patterns & attributes to build machine learning models.

They are a part of a brainstorming team with product managers on customer needs & are expected to come up with new ideas. AI/ML Engineers monitor and fine-tuning ML models to improving team productivity.

Task-Oriented Machine Learning

A machine learning engineer monitors, optimizes, tests, trains, and deploys machine learning algorithms for specific tasks. At some places, ML engineers are expected to implement and carry on more ML-specific transformations, such as outlier detection, dimensionality reduction, feature engineering, missing value imputation, normalization, etc. Once the data is ready for the ML algorithm, the ML engineer is responsible for setting the training algorithm appropriately and executing it in a reasonable time to produce a satisfactory performance.

Grow and Learn Machine Learning with Imarticus Learning:

Explore the opportunity to learn Machine learning from the Best ML & AI Course that boosts your Data Science Career. An industry approved program designed by E&ICT Academy, IIT Guwahati, and Imarticus Learning for future Data Scientists & ML Engineers, this program builds a strong foundation of Data Science concepts, and industry experts will help you learn the practical implementation of Machine Learning, Deep Learning, and AI techniques through real-world projects from diverse industries.

This course goes a long way towards helping you unlock lucrative career opportunities in the coveted fields of Data Science and Artificial Intelligence. The 9-month extensive program will help you prepare for the Data Scientist, Data Analyst, Machine Learning Engineer, and AI Engineer roles.

The objective of this state-of-the-art Artificial Intelligence and Machine Learning Certification Course is to perfectly prepare you for the AI and Machine Learning job roles you aspire for

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